Abstract

The temporal correlation hypothesis proposes that neurons signal mutual inclusion in complex features, such as extended contours, by phase-locking their firing [C. M. Gray and W. Singer, Proc. Natl. Acad. Sci. USA 86, 1698 (1989)]. Although this hypothesis remains controversial, a number of recent psychophysical studies have suggested that temporal correlation among features can indeed promote perceptual grouping. In particular, subjects are better at detecting extended visual contours embedded within a field of distractor elements when a small delay is present between a cycling presentation of the contour and the background [Nature 394, 179 (1988)]. We have replicated this finding and examined three potentially confounding factors. First, we controlled local density and used more curved contours composed of bandpass elements to confirm that the effect was associated with contour integration and not with the operation of coarse-scale spatial filters. Second, we minimized the effects of saccadic eye movements (which could combine with the flicker of the asynchronous display to introduce motion cues at the contour location) both by using a fixation marker that was visible only when observers made a saccade (allowing them to reject these trials) and by retinally stabilizing the stimulus. We report that eye movements contribute to the effect. Third, we asked if either visible persistence or transients at the onset and the offset of the asynchronous stimuli might contribute to the effect. We report that the effect is largely abolished by the inclusion of prestimulus and poststimulus masks and is entirely abolished by ramping the contrast of the stimulus on and off. Neither ramping, masking, nor stabilization should specifically disrupt a contour-binding scheme based on temporal synchrony, and we conclude that it is the transient component at the onset and the offset of these stimuli that is responsible for the reported advantage for asynchronous presentation.

© 2002 Optical Society of America

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  1. C. M. Gray, W. Singer, “Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex,” Proc. Natl. Acad. Sci. USA 86, 1698–1702 (1989).
    [CrossRef] [PubMed]
  2. P. Milner, “A model for visual shape recognition,” Psychol. Rev. 81, 521–535 (1974).
    [CrossRef] [PubMed]
  3. W. Singer, C. M. Gray, “Visual feature integration and the temporal correlation hypothesis,” Annu. Rev. Neurosci. 18, 555–586 (1995).
    [CrossRef] [PubMed]
  4. C. von der Malsburg, in Models of Neural Networks II, E. Domany, J. L. van Hemmen, K. Schulten, eds. (Springer-Verlag, Berlin, 1981).
  5. G. M. Ghose, R. D. Freeman, “Oscillatory discharge in the visual system: does it have a functional role?” J. Neurophysiol. 68, 1558–1574 (1992).
    [PubMed]
  6. M. N. Shadlen, J. A. Movshon, “Synchrony unbound: a critical evaluation of the temporal binding hypothesis,” Neuron 24, 67–77, 111–125 (1999).
    [CrossRef]
  7. S. H. Lee, R. Blake, “Visual form created solely from temporal structure,” Science 284, 1165–1168 (1999).
    [CrossRef] [PubMed]
  8. E. H. Adelson, H. Farid, “Filtering reveals form in temporally structured displays,” Science 286, 2231a (1999).
    [CrossRef]
  9. U. Leonards, W. Singer, M. Fahle, “The influence of temporal phase differences on texture segmentation,” Vision Res. 36, 2689–2697 (1996).
    [CrossRef] [PubMed]
  10. D. C. Kiper, K. R. Gegenfurtner, J. A. Movshon, “Cortical oscillatory responses do not affect visual segmentation,” Vision Res. 36, 539–544 (1996).
    [CrossRef] [PubMed]
  11. M. Usher, N. Donnelly, “Visual synchrony affects binding and segmentation in perception,” Nature (London) 394, 179–182 (1998).
    [CrossRef]
  12. D. C. Rogers-Ramachandran, V. S. Ramachandran, “Phantom contours: selective stimulation of the magnocellular pathways in man,” Invest. Ophthalmol. Visual Sci. Suppl. 32, 1034 (1991).
  13. M. Fahle, “Figure–ground discrimination from temporal information,” Proc. R. Soc. London Ser. B 254, 199–203 (1993).
    [CrossRef]
  14. D. J. Field, A. Hayes, R. F. Hess, “Contour integration by the human visual system: evidence for a local ‘association field’,” Vision Res. 33, 173–193 (1993).
    [CrossRef] [PubMed]
  15. R. F. Hess, S. C. Dakin, “Absence of contour linking in peripheral vision,” Nature (London) 390, 602–604 (1997).
    [CrossRef]
  16. R. J. Watt, “Scanning from coarse to fine spatial-scales in the human visual system after the onset of the stimulus,” J. Opt. Soc. Am. A 4, 2006–2021 (1987).
    [CrossRef] [PubMed]
  17. D. H. Brainard, “The Psychophysics Toolbox,” Spatial Vision 10, 433–436 (1997).
    [CrossRef] [PubMed]
  18. D. G. Pelli, “The VideoToolbox software for visual psychophysics: transforming number into movies,” Spatial Vision 10, 437–442 (1997).
    [CrossRef]
  19. Orientation bandwidths were estimated by constructing an orientation histogram from the image’s Fourier transform; each point in the transform contributes in proportion to its energy. The resulting histogram was fitted with a Gaussian function; the FWHH bandwidth was 2.35× the σ parameter of this function.
  20. S. C. Dakin, R. F. Hess, “Spatial-frequency tuning of visual contour integration,” J. Opt. Soc. Am. A 15, 1486–1499 (1998).
    [CrossRef]
  21. S. C. Dakin, R. F. Hess, “Contour integration and scale combination processes in visual edge detection,” Spatial Vision 12, 309–327 (1999).
    [CrossRef] [PubMed]
  22. W. H. A. Beaudot, “Role of onset asynchrony in contour integration,” Vision Res. 42, 1–9 (2002).
    [CrossRef] [PubMed]

2002 (1)

W. H. A. Beaudot, “Role of onset asynchrony in contour integration,” Vision Res. 42, 1–9 (2002).
[CrossRef] [PubMed]

1999 (4)

S. C. Dakin, R. F. Hess, “Contour integration and scale combination processes in visual edge detection,” Spatial Vision 12, 309–327 (1999).
[CrossRef] [PubMed]

M. N. Shadlen, J. A. Movshon, “Synchrony unbound: a critical evaluation of the temporal binding hypothesis,” Neuron 24, 67–77, 111–125 (1999).
[CrossRef]

S. H. Lee, R. Blake, “Visual form created solely from temporal structure,” Science 284, 1165–1168 (1999).
[CrossRef] [PubMed]

E. H. Adelson, H. Farid, “Filtering reveals form in temporally structured displays,” Science 286, 2231a (1999).
[CrossRef]

1998 (2)

M. Usher, N. Donnelly, “Visual synchrony affects binding and segmentation in perception,” Nature (London) 394, 179–182 (1998).
[CrossRef]

S. C. Dakin, R. F. Hess, “Spatial-frequency tuning of visual contour integration,” J. Opt. Soc. Am. A 15, 1486–1499 (1998).
[CrossRef]

1997 (3)

R. F. Hess, S. C. Dakin, “Absence of contour linking in peripheral vision,” Nature (London) 390, 602–604 (1997).
[CrossRef]

D. H. Brainard, “The Psychophysics Toolbox,” Spatial Vision 10, 433–436 (1997).
[CrossRef] [PubMed]

D. G. Pelli, “The VideoToolbox software for visual psychophysics: transforming number into movies,” Spatial Vision 10, 437–442 (1997).
[CrossRef]

1996 (2)

U. Leonards, W. Singer, M. Fahle, “The influence of temporal phase differences on texture segmentation,” Vision Res. 36, 2689–2697 (1996).
[CrossRef] [PubMed]

D. C. Kiper, K. R. Gegenfurtner, J. A. Movshon, “Cortical oscillatory responses do not affect visual segmentation,” Vision Res. 36, 539–544 (1996).
[CrossRef] [PubMed]

1995 (1)

W. Singer, C. M. Gray, “Visual feature integration and the temporal correlation hypothesis,” Annu. Rev. Neurosci. 18, 555–586 (1995).
[CrossRef] [PubMed]

1993 (2)

M. Fahle, “Figure–ground discrimination from temporal information,” Proc. R. Soc. London Ser. B 254, 199–203 (1993).
[CrossRef]

D. J. Field, A. Hayes, R. F. Hess, “Contour integration by the human visual system: evidence for a local ‘association field’,” Vision Res. 33, 173–193 (1993).
[CrossRef] [PubMed]

1992 (1)

G. M. Ghose, R. D. Freeman, “Oscillatory discharge in the visual system: does it have a functional role?” J. Neurophysiol. 68, 1558–1574 (1992).
[PubMed]

1991 (1)

D. C. Rogers-Ramachandran, V. S. Ramachandran, “Phantom contours: selective stimulation of the magnocellular pathways in man,” Invest. Ophthalmol. Visual Sci. Suppl. 32, 1034 (1991).

1989 (1)

C. M. Gray, W. Singer, “Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex,” Proc. Natl. Acad. Sci. USA 86, 1698–1702 (1989).
[CrossRef] [PubMed]

1987 (1)

1974 (1)

P. Milner, “A model for visual shape recognition,” Psychol. Rev. 81, 521–535 (1974).
[CrossRef] [PubMed]

Adelson, E. H.

E. H. Adelson, H. Farid, “Filtering reveals form in temporally structured displays,” Science 286, 2231a (1999).
[CrossRef]

Beaudot, W. H. A.

W. H. A. Beaudot, “Role of onset asynchrony in contour integration,” Vision Res. 42, 1–9 (2002).
[CrossRef] [PubMed]

Blake, R.

S. H. Lee, R. Blake, “Visual form created solely from temporal structure,” Science 284, 1165–1168 (1999).
[CrossRef] [PubMed]

Brainard, D. H.

D. H. Brainard, “The Psychophysics Toolbox,” Spatial Vision 10, 433–436 (1997).
[CrossRef] [PubMed]

Dakin, S. C.

S. C. Dakin, R. F. Hess, “Contour integration and scale combination processes in visual edge detection,” Spatial Vision 12, 309–327 (1999).
[CrossRef] [PubMed]

S. C. Dakin, R. F. Hess, “Spatial-frequency tuning of visual contour integration,” J. Opt. Soc. Am. A 15, 1486–1499 (1998).
[CrossRef]

R. F. Hess, S. C. Dakin, “Absence of contour linking in peripheral vision,” Nature (London) 390, 602–604 (1997).
[CrossRef]

Donnelly, N.

M. Usher, N. Donnelly, “Visual synchrony affects binding and segmentation in perception,” Nature (London) 394, 179–182 (1998).
[CrossRef]

Fahle, M.

U. Leonards, W. Singer, M. Fahle, “The influence of temporal phase differences on texture segmentation,” Vision Res. 36, 2689–2697 (1996).
[CrossRef] [PubMed]

M. Fahle, “Figure–ground discrimination from temporal information,” Proc. R. Soc. London Ser. B 254, 199–203 (1993).
[CrossRef]

Farid, H.

E. H. Adelson, H. Farid, “Filtering reveals form in temporally structured displays,” Science 286, 2231a (1999).
[CrossRef]

Field, D. J.

D. J. Field, A. Hayes, R. F. Hess, “Contour integration by the human visual system: evidence for a local ‘association field’,” Vision Res. 33, 173–193 (1993).
[CrossRef] [PubMed]

Freeman, R. D.

G. M. Ghose, R. D. Freeman, “Oscillatory discharge in the visual system: does it have a functional role?” J. Neurophysiol. 68, 1558–1574 (1992).
[PubMed]

Gegenfurtner, K. R.

D. C. Kiper, K. R. Gegenfurtner, J. A. Movshon, “Cortical oscillatory responses do not affect visual segmentation,” Vision Res. 36, 539–544 (1996).
[CrossRef] [PubMed]

Ghose, G. M.

G. M. Ghose, R. D. Freeman, “Oscillatory discharge in the visual system: does it have a functional role?” J. Neurophysiol. 68, 1558–1574 (1992).
[PubMed]

Gray, C. M.

W. Singer, C. M. Gray, “Visual feature integration and the temporal correlation hypothesis,” Annu. Rev. Neurosci. 18, 555–586 (1995).
[CrossRef] [PubMed]

C. M. Gray, W. Singer, “Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex,” Proc. Natl. Acad. Sci. USA 86, 1698–1702 (1989).
[CrossRef] [PubMed]

Hayes, A.

D. J. Field, A. Hayes, R. F. Hess, “Contour integration by the human visual system: evidence for a local ‘association field’,” Vision Res. 33, 173–193 (1993).
[CrossRef] [PubMed]

Hess, R. F.

S. C. Dakin, R. F. Hess, “Contour integration and scale combination processes in visual edge detection,” Spatial Vision 12, 309–327 (1999).
[CrossRef] [PubMed]

S. C. Dakin, R. F. Hess, “Spatial-frequency tuning of visual contour integration,” J. Opt. Soc. Am. A 15, 1486–1499 (1998).
[CrossRef]

R. F. Hess, S. C. Dakin, “Absence of contour linking in peripheral vision,” Nature (London) 390, 602–604 (1997).
[CrossRef]

D. J. Field, A. Hayes, R. F. Hess, “Contour integration by the human visual system: evidence for a local ‘association field’,” Vision Res. 33, 173–193 (1993).
[CrossRef] [PubMed]

Kiper, D. C.

D. C. Kiper, K. R. Gegenfurtner, J. A. Movshon, “Cortical oscillatory responses do not affect visual segmentation,” Vision Res. 36, 539–544 (1996).
[CrossRef] [PubMed]

Lee, S. H.

S. H. Lee, R. Blake, “Visual form created solely from temporal structure,” Science 284, 1165–1168 (1999).
[CrossRef] [PubMed]

Leonards, U.

U. Leonards, W. Singer, M. Fahle, “The influence of temporal phase differences on texture segmentation,” Vision Res. 36, 2689–2697 (1996).
[CrossRef] [PubMed]

Milner, P.

P. Milner, “A model for visual shape recognition,” Psychol. Rev. 81, 521–535 (1974).
[CrossRef] [PubMed]

Movshon, J. A.

M. N. Shadlen, J. A. Movshon, “Synchrony unbound: a critical evaluation of the temporal binding hypothesis,” Neuron 24, 67–77, 111–125 (1999).
[CrossRef]

D. C. Kiper, K. R. Gegenfurtner, J. A. Movshon, “Cortical oscillatory responses do not affect visual segmentation,” Vision Res. 36, 539–544 (1996).
[CrossRef] [PubMed]

Pelli, D. G.

D. G. Pelli, “The VideoToolbox software for visual psychophysics: transforming number into movies,” Spatial Vision 10, 437–442 (1997).
[CrossRef]

Ramachandran, V. S.

D. C. Rogers-Ramachandran, V. S. Ramachandran, “Phantom contours: selective stimulation of the magnocellular pathways in man,” Invest. Ophthalmol. Visual Sci. Suppl. 32, 1034 (1991).

Rogers-Ramachandran, D. C.

D. C. Rogers-Ramachandran, V. S. Ramachandran, “Phantom contours: selective stimulation of the magnocellular pathways in man,” Invest. Ophthalmol. Visual Sci. Suppl. 32, 1034 (1991).

Shadlen, M. N.

M. N. Shadlen, J. A. Movshon, “Synchrony unbound: a critical evaluation of the temporal binding hypothesis,” Neuron 24, 67–77, 111–125 (1999).
[CrossRef]

Singer, W.

U. Leonards, W. Singer, M. Fahle, “The influence of temporal phase differences on texture segmentation,” Vision Res. 36, 2689–2697 (1996).
[CrossRef] [PubMed]

W. Singer, C. M. Gray, “Visual feature integration and the temporal correlation hypothesis,” Annu. Rev. Neurosci. 18, 555–586 (1995).
[CrossRef] [PubMed]

C. M. Gray, W. Singer, “Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex,” Proc. Natl. Acad. Sci. USA 86, 1698–1702 (1989).
[CrossRef] [PubMed]

Usher, M.

M. Usher, N. Donnelly, “Visual synchrony affects binding and segmentation in perception,” Nature (London) 394, 179–182 (1998).
[CrossRef]

von der Malsburg, C.

C. von der Malsburg, in Models of Neural Networks II, E. Domany, J. L. van Hemmen, K. Schulten, eds. (Springer-Verlag, Berlin, 1981).

Watt, R. J.

Annu. Rev. Neurosci. (1)

W. Singer, C. M. Gray, “Visual feature integration and the temporal correlation hypothesis,” Annu. Rev. Neurosci. 18, 555–586 (1995).
[CrossRef] [PubMed]

Invest. Ophthalmol. Visual Sci. Suppl. (1)

D. C. Rogers-Ramachandran, V. S. Ramachandran, “Phantom contours: selective stimulation of the magnocellular pathways in man,” Invest. Ophthalmol. Visual Sci. Suppl. 32, 1034 (1991).

J. Neurophysiol. (1)

G. M. Ghose, R. D. Freeman, “Oscillatory discharge in the visual system: does it have a functional role?” J. Neurophysiol. 68, 1558–1574 (1992).
[PubMed]

J. Opt. Soc. Am. A (2)

Nature (London) (2)

M. Usher, N. Donnelly, “Visual synchrony affects binding and segmentation in perception,” Nature (London) 394, 179–182 (1998).
[CrossRef]

R. F. Hess, S. C. Dakin, “Absence of contour linking in peripheral vision,” Nature (London) 390, 602–604 (1997).
[CrossRef]

Neuron (1)

M. N. Shadlen, J. A. Movshon, “Synchrony unbound: a critical evaluation of the temporal binding hypothesis,” Neuron 24, 67–77, 111–125 (1999).
[CrossRef]

Proc. Natl. Acad. Sci. USA (1)

C. M. Gray, W. Singer, “Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex,” Proc. Natl. Acad. Sci. USA 86, 1698–1702 (1989).
[CrossRef] [PubMed]

Proc. R. Soc. London Ser. B (1)

M. Fahle, “Figure–ground discrimination from temporal information,” Proc. R. Soc. London Ser. B 254, 199–203 (1993).
[CrossRef]

Psychol. Rev. (1)

P. Milner, “A model for visual shape recognition,” Psychol. Rev. 81, 521–535 (1974).
[CrossRef] [PubMed]

Science (2)

S. H. Lee, R. Blake, “Visual form created solely from temporal structure,” Science 284, 1165–1168 (1999).
[CrossRef] [PubMed]

E. H. Adelson, H. Farid, “Filtering reveals form in temporally structured displays,” Science 286, 2231a (1999).
[CrossRef]

Spatial Vision (3)

S. C. Dakin, R. F. Hess, “Contour integration and scale combination processes in visual edge detection,” Spatial Vision 12, 309–327 (1999).
[CrossRef] [PubMed]

D. H. Brainard, “The Psychophysics Toolbox,” Spatial Vision 10, 433–436 (1997).
[CrossRef] [PubMed]

D. G. Pelli, “The VideoToolbox software for visual psychophysics: transforming number into movies,” Spatial Vision 10, 437–442 (1997).
[CrossRef]

Vision Res. (4)

W. H. A. Beaudot, “Role of onset asynchrony in contour integration,” Vision Res. 42, 1–9 (2002).
[CrossRef] [PubMed]

D. J. Field, A. Hayes, R. F. Hess, “Contour integration by the human visual system: evidence for a local ‘association field’,” Vision Res. 33, 173–193 (1993).
[CrossRef] [PubMed]

U. Leonards, W. Singer, M. Fahle, “The influence of temporal phase differences on texture segmentation,” Vision Res. 36, 2689–2697 (1996).
[CrossRef] [PubMed]

D. C. Kiper, K. R. Gegenfurtner, J. A. Movshon, “Cortical oscillatory responses do not affect visual segmentation,” Vision Res. 36, 539–544 (1996).
[CrossRef] [PubMed]

Other (2)

C. von der Malsburg, in Models of Neural Networks II, E. Domany, J. L. van Hemmen, K. Schulten, eds. (Springer-Verlag, Berlin, 1981).

Orientation bandwidths were estimated by constructing an orientation histogram from the image’s Fourier transform; each point in the transform contributes in proportion to its energy. The resulting histogram was fitted with a Gaussian function; the FWHH bandwidth was 2.35× the σ parameter of this function.

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Figures (6)

Fig. 1
Fig. 1

Examples of the stimuli. Subjects were required to identify which quadrant of a movie display contained an embedded contour. In the asynchronous condition frames alternated between (a) an image containing a contour and (b) a set of distractor elements. (c) In the synchronous condition the contour and the distractor were presented simultaneously, and this frame alternated with a blank field. (d) To limit the effects of visible persistence, a mask preceded and followed the stimulus in certain conditions. This was a phase-randomized version of a typical contour stimulus.

Fig. 2
Fig. 2

(a), (b) The fixation marker consisted of a movie sequence alternating, at 60 reversals per second, between the two images shown. Thus involuntary eye movements were revealed by the appearance of the bull’s-eye grating, which was otherwise invisible below the cross hairs. (c) Frame sequence of stimuli (Con=contour presented alone, Dis=distractors presented alone, Con & Dis=contour embedded in distractors, Fix=fixation marker). All stimuli movies were played at 120 frames per second (f.p.s.), but stimulus frames were doubled up to give an effective frame rate of 60 f.p.s. Both conditions consisted of two interleaved sequences. In the asynchronous condition, contour and distractor elements were interleaved. In the synchronous condition, contour and distractor appeared together within a frame and were interleaved with blanks. Qualitatively, conditions cannot be distinguished from one another.

Fig. 3
Fig. 3

Results from experiment 1: probability of detecting a contour as a function of stimulus exposure duration. Results from the five subjects are given in (a)–(e), and (f) gives the average performance. The contour was presented either synchronously (circles) or asynchronously (upward-pointing triangles) with the background/distractor elements. Results indicate a sizable and generally statistically significant advantage for asynchronous presentation. The first two plots include data from two additional control conditions examining the effect of reversing the order of asynchronous presentation (upward-pointing triangles) and reducing the visible flicker within the synchronous condition (squares). Neither manipulation alters performance significantly from the respective conditions.

Fig. 4
Fig. 4

Results from experiment 2: contour detection as a function of the exposure duration (stimulus movie length) for stimuli that have been premasked and postmasked with filtered noise. Comparing masked with unmasked conditions (closed symbols versus solid and dashed lines), one can clearly see that there is a moderate reduction in performance for synchronous presentation, particularly at shorter exposure times, but that there is an enormous reduction in performance for asynchronous presentation across all exposure times. With masking, the asynchronous advantage is no longer statistically significant for any subject at any exposure time.

Fig. 5
Fig. 5

Contour detection performance measured with two subjects for synchronous (light bars) and asynchronous (dark bars) presentation. Stimuli were viewed monocularly through the optical apparatus of an image stabilizer and either were presented abruptly or were smoothly contrast ramped to remove transient structure at the onset and the offset. The left-hand and right-hand sets of four bars show data with and without image stabilization, respectively. The asynchronous advantage is present for unstabilized monocular viewing but is abolished by contrast ramping and diminished by retinal stabilization.

Fig. 6
Fig. 6

Open symbols show contour detection measured as a function of the orientation difference between the components of the contour and the local contour direction. Embedded images show examples of the (isolated) contour with various orientation offsets. Note that the advantage for asynchronous presentation is particularly pronounced when elements are coaligned. However, this may be due not to coalignment but to the effect of orientation bandwidth, which covaries with orientation offset. Filled symbols show detection performance for a coaligned contour where the elements have been “shortened” so that the global orientation bandwidth is now matched to the 90° orientation offset condition. The asynchronous advantage is now abolished.

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